This research project involves the design and implementation of an anxiety management application for transmission on the iPhone. The application employs cognitive behavioral therapy (CBT) methodology and is designed for the 16 to 25 year old demographic. Normally used in face to face therapeutic interactions, the use of a mobile application is unique in that it supplies the patient with just in time access to the therapeutic techniques necessary to manage their anxiety.
Text mining is the process of automatically extracting knowledge from unstructured, natural language documents. It aims to support users in dealing with large amount of textual information. Examples for specific text mining tasks are entity detection, summarization, and opinion mining. Due to the complexity and ambiguity of natural language, this analysis is broken down into individual processing steps, which are based on the techniques from the fields of machine learning, natural language processing, and semantic computing.
The industrial partner, Digido, is interested in developing and marketing exercise games targeted at children that leverage the increased prevalence of smartphones and their sensing and computational capacity, including: their ability to detect activity levels; their increasing use as a gaming platform; and their integration with social media and online communities. However, current activity sensing and classification techniques are too limiting for use in smartphone-based exergames for children.
With dramatic improvements in vessel performance and tactical systems of high speed crafts in recent years, naval, coast guard and law enforcement agencies increasingly task them to complete a growing range of operational objectives. The combination of faster vessels, more sophisticated systems and extended responsibilities has driven fleet operators to re-examine how their boat crews are trained.
In an alien or possibly hostile environment, the situation awareness of a remote robot operator will be limited. Map information may not be known beforehand. The site may also be in a dynamic state where changes occur in the surrounding in any moment. The main objective of this project is to develop novel technologies to increase situation awareness of remote robot operators and their ability to intuitively interact with the robots for more efficient operations.
In this project we attempt to research and develop from ground up a scalable distributed computing based recommendation engine using machine learning. A computer science student from the University of Toronto will work with Side Effects Software at their Toronto office to implement the research intensive recommendation engine algorithm and integrate it in the smart asset online store. We expect and hope that this will result in high quality recommendation, is scalable and has a strong foundation in statistical machine learning based algorithm approach.
Small teams of mobile robots provide nowadays the ability to assist wireless sensor networks in many threatening scenarios that unexpectedly arise during their operational lifetime. The perceived risk or vulnerability that the network is exposed to triggers an immediate, corporate action from the robotic agents (actuators). We focus on a sort of robots which are able to carry static sensors and deploy them all over the field.
